Research And Application Of Decision Support Techniques In Enterprise Sales System

Enterprise has paid more and more attentions to the information construction due to the rapid development of computer technology and information processing. Enterprise not satisfying with a simple data processing and reporting, hope for a business intelligence which can apply some implicit information by digging knowledge out of data.The concept of decision support is proposed for this demand, they convert the huge historical data to knowledge, which can help the policymakers make decisions.Decision support technology includes Data Warehouse, OLAP and Data Mining. Data warehouse prepare a lot of valid data for decision-making by integrating data from all aspects of the enterprise. OLAP analysis the data in many different points to provide a global view of enterprise's data for the policymaker, and the data mining find valuable and potential information form the historical data, which can provide evidence-based and scientific reference for the enterprise managers.The paper is based on the demand of a floor import sales company.It uses the historical data to contribute properly mathematical model on the existing information manage project, then apply the key technology of DSS to construct an analysis model of historical data and a forecast model of new good's profit.The policymakers can use the analysis model to analyze the dead or peak season which can help them draw up the right sales plan, just like cut down the price in dead seasons, make properly orders, and so on. The new goods profit forecasting model is used before a new good's pulling in, it can forecast the good's sales quantity and profit for the managers, provides a powerful support for the manager to make right development strategies.